Detection and Resolution of Motion Conflict in Visual Inertial Odometry
| Autor: | Benzun Pious Wisely Babu, David Cyganski, James Duckworth, Soohwan Kim |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Inertial frame of reference
Computer science business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Simultaneous localization and mapping Motion (physics) Odometry Inertial measurement unit Robustness (computer science) Trajectory Computer vision Artificial intelligence Visual odometry business |
| Zdroj: | ICRA |
| DOI: | 10.1109/icra.2018.8460870 |
| Popis: | In this paper, we present a novel method to detect and resolve motion conflicts in visual-inertial odometry. Recently, it has been common to integrate an IMU sensor with visual odometry in order to improve localization accuracy and robustness. However, when a disagreement between the two sensor modalities occurs, the localization accuracy reduces drastically and leads to irreversible errors. In such conditions, multiple motion estimates based on the set of observations used are possible. This creates a conflict (motion conflict) in determining which observations to use for accurate ego-motion estimation. Therefore, we present a method to detect motion conflicts based on per-frame positional estimate discrepancy and per-landmark reprojection errors. Additionally, we also present a method to resolve motion conflicts by eliminating inconsistent IMU and landmark measurements. Finally, we implement Motion Conflict aware Visual Inertial Odometry (MC-VIO) by combining both detection and resolution of motion conflicts. We perform quantitative and qualitative evaluation of MC-VIO on visually and inertially challenging datasets. Experimental results indicate that the MC-VIO algorithm reduces the increase in absolute trajectory error by 80% and the relative pose error by 60% for scenes with motion conflict, in comparison to the state-of-the-art reference VIO algorithm. |
| Databáze: | OpenAIRE |
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